Associations of household dampness and cold exposure with cardiovascular disease and symptoms among elderly people in Chongqing and Beijing

Guo, Miao; Yu, Wei; Zhang, Yan; Li, Baizhan; Zhou, Hu; Du, Chenqiu

doi:10.1016/j.buildenv.2023.110079

Cited by 4 publications

(2 citation statements)

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“…According to our previous home investigations and fungal measurements in air and dust in typical residences in Chongqing, China [39,40], as well as in other studies [41,42], Aspergillus niger is a common fungal species that is widely detected in residential environments, causing some allergic or respiratory diseases due to the emitted allergens [16,43]. Therefore, Aspergillus niger (ATCC 16404, same as AS3.3928, American Type Culture Collection (ATCC)) was chosen as inoculation strain, as shown in Figure 1a.…”

Section: Mold Strains and Inoculationsmentioning

confidence: 95%

“…Aspergillus niger is a common fungal species that is widely detected in residential environments, causing some allergic or respiratory diseases due to the emitted allergens [16,43]. Therefore, Aspergillus niger (ATCC 16404, same as AS3.3928, American Type Culture Collection (ATCC)) was chosen as inoculation strain, as shown in Figure 1a.…”

Section: Mold Strains and Inoculationsmentioning

confidence: 99%

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A Predictive Model for the Growth Diameter of Mold under Different Temperatures and Relative Humidities in Indoor Environments

Wang,

Mei,

Wang

et al. 2024

Buildings

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A substantial body of evidence suggests that indoor mold exposure is a cause of allergic and respiratory diseases in humans. While models exist for assessing the risk of mold growth on building materials, few study the characteristics of mold growth after germination. This study conducted mold growth experiments in a constant temperature chamber, using four temperature settings of 15, 20, 25 and 30 °C, and three relative humidities of 56 to 61%, 75 to 76% and 83 to 86%. A mold growth prediction model was established using temperature and relative humidity. The accuracy of the model was verified by comparing the sampling and the predicted values in a laboratory environment. The results indicated that reducing the environmental temperature and relative humidity could significantly inhibit the growth of mold, although the inhibitory effects varied. Temperature might play a more critical role. At higher temperatures (25 °C and 30 °C), the growth rate and lag time of mold tended to be consistent and there were differences in the maximum diameter. In the predictive model, the polynomial secondary model for the maximum growth rate and lag time and the Arrhenius–Davey secondary model for the maximum diameter (A) had good predictive effects (Adj.R2 > 0.850). It is speculated that temperature is the key factor affecting the maximum growth diameter of mold. The mold growth prediction model could better predict the growth of mold in actual environments without wind Adj.R2 > 0.800), but the accuracy of the model decreased under windy conditions (wind velocity < 1 m/s). The mold growth predictive model we established could be used to predict the growth characteristics of mold in windless environments. It also provides control suggestions for the regulation of temperature and relative humidity in indoor environments, supporting indoor thermal environment management and pollutant control, and ensuring indoor human health.

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